The Metadata Assistant: How Red Hat is using generative AI to make web content easier to find and use

The Metadata Assistant: How Red Hat is using generative AI to make web content easier to find and use Facing challenges with metadata accuracy How Red Hat's Metadata Assistant helps How it works: Relieving Red Hatters from long forms and tedious tasks Conclusion Get started with AI Inference About the authors Anna McHugh Gail Vadia More like this Blog post Blog post Blog post Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share Most of us rely on good web metadata every day, perhaps hundreds of times a day, without ever realizing it. While we don’t all see metadata, it’s present on every webpage, providing details for categorizing content. Search and information retrieval software—from content management systems and search engines to generative AI (gen AI) chatbots—all depend on metadata to categorize, interpret, and display content to users. In some ways, metadata is like the classification system librarians use to place books on shelves so that visitors can find them. Much like a library catalog, good web metadata makes content easier to find and use because it has consistent, meaningful labels. At Red Hat, we maintain dozens of websites with tens of thousands of pages and millions of metadata selections. To help manage it all, we’ve developed a new internal generative AI (gen AI) tool: the Metadata Assistant. Despite our best efforts to stay organized, we struggle to make accurate and consistent tags. The overwhelming amount of content to classify can feel like a messy, towering pile of books instead of an organized library where you can browse the shelves by meaningful categories. Red Hatters must consider more than 150 taxonomy choices across several parent categories, like products, topics, industries, regions, and partners when classifying their content. Our product portfolio is complex, with products frequently being added, discontinued, or renamed. Metadata best practices can be tricky for teams to keep up with.